In recent years, 3D pose estimation has attracted a great deal of interest from researchers due to its widespread application in a range of fields, including video analysis, camera surveillance, human-computer interaction, virtual/augmented reality, etc. Great successes have been achieved in monocular 3D human pose estimation, especially when dealing with a single person in an image[1]}, [2]}, [3]}, [4]}, [5]}, [6]}. However, when it comes to real-world scenarios, inferring poses can be much harder, especially when multiple persons are present in the scene. This is because body joints are often occluded by other objects or people. For this reason, monocular 3D multi-person pose estimation (3D-MPE) is still a challenging problem, yet, robustness to such occlusions is critical to real-world applications.
